Marginal Fit of Three Commonly Used Veneers for Smile Enhancement: An In Vitro Study.

Area of Science:

• Dental Materials Science
• Prosthodontics
• Biomaterials Engineering

Background:

• Accurate marginal fit of dental veneers is crucial for long-term restoration success and preventing secondary caries.
• Commonly used veneer materials include indirect composite, pressable ceramic, and CAD/CAM fabricated ceramics.
• Variations in fabrication techniques and materials can influence the marginal adaptation of veneers.

Purpose of the Study:

• To compare the marginal fit of three prevalent dental veneer types: indirect composite veneers (ICV), pressable ceramic veneers (PCV), and computer-aided designing/computer-aided manufacturing (CAD/CAM) ceramic veneers.
• To quantify marginal discrepancies at specific tooth margin locations for each veneer type.
• To determine which veneer material exhibits the most clinically acceptable marginal fit.

Main Methods:

• Standardized preparation of a maxillary central incisor embedded in acrylic resin.
• Fabrication of 30 veneers across three groups: ICV, PCV (lithium disilicate), and CAD/CAM ceramic (lithium disilicate).
• Evaluation of marginal discrepancy using stereomicroscopy at defined labial and palatal margin points, followed by statistical analysis (ANOVA, Tukey's test).

Main Results:

• Pressable ceramic veneers (PCV) demonstrated the smallest mean marginal discrepancies (48.2 µm cervical, 40.58 µm palatal).
• CAD/CAM ceramic veneers showed moderate discrepancies (94.24 µm cervical, 52.72 µm palatal).
• Indirect composite veneers (ICV) exhibited the largest marginal discrepancies (189.24 µm cervical, 79.01 µm palatal).

Conclusions:

• Pressable ceramic veneers offer the best marginal fit among the tested materials, followed by CAD/CAM ceramic veneers.
• Indirect composite veneers showed the poorest marginal fit.
• Both PCV and CAD/CAM ceramic veneers exhibited marginal discrepancies within clinically acceptable ranges, highlighting the importance of material selection for predictable clinical performance.